Qualidade de solos em agroecossistemas camponeses no território da Borborema-PB

• Ano de defesa: 2020
• Autor(a) principal: Melo, David Marx Antunes de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal da Paraíba; Brasil; Agricultura; Programa de Pós-Graduação em Ciências Agrárias (Agroecologia); UFPB
• Palavras-chave em Português: Sistemas Camponeses; Indicadores; Técnicas multivariadas; Subsistemas; Indicators; Multivariate techniques; CNPQ::CIENCIAS AGRARIAS
• Link de acesso: https://repositorio.ufpb.br/jspui/handle/123456789/24551

Soil quality is the basis for the sustainability of Peasant Production Systems (SCP). It can be expressed through indicators and indices that allow the identification of the most relevant attributes. The objective was this study analyzes to quali-quantitatively analyze the soil quality in SCP in the territory of Borborema (PB). The research was carried out in the territory of Borborema, in the municipalities of Solânea (agro-ecosystem A), Casserengue (agro-ecosystem B) and Serraria (agro-ecosystem C). Samples were collected at a depth of 0-20 cm and analyzed for quantitative (chemical and physical attributes of the soil) and qualitative (Pfeiffer chromatography (CP) and Rapid Field Test) variables. The data were treated using multivariate techniques (hierarchical grouping, Kruskal Wallis test together with Spearman's correlation analysis, Principal Component Analysis (ACP) and Logistic Regression (RL)). From this, the soil quality index (IQS) was determined for all SCP's. The minimum set of quantitative indicators to assess the QSI was composed of P, Ca + 2, Al + 3, V, m, Sand, Silte, SB and H + Al, while the qualitative ones were the External Zone, Soil Structure, Compaction, Erosion, Cover, Invertebrates, Inner zone and Harmony. In general, the IQS of the analyzed SCPs were low for both methods of analysis. By the quantitative analysis the IQS had the following order B> C> A, while by the qualitative variables the IQS was A> C> B. Finally, the RL analysis showed significant correlations between quantitative and qualitative (CP) variables. This result in particular, further supports the use of CP as an expeditious method to analyze soil quality in SCP. CP can be used as a subsidy for decision making and to increase the perception of the soil by the peasants as a living component of the landscape.